Merge pull request #116 from honno/minor-fixes

Minor fixes

array_api_tests/test_creation_functions.py

@@ -409,43 +409,20 @@ def test_full_like(x, fill_value, kw):
 finite_kw = {"allow_nan": False, "allow_infinity": False}
 
 
-def int_stops(
-    start: int, num, dtype: DataType, endpoint: bool
-) -> st.SearchStrategy[int]:
-    min_gap = num
-    if endpoint:
-        min_gap += 1
-    m, M = dh.dtype_ranges[dtype]
-    max_pos_gap = M - start
-    max_neg_gap = start - m
-    max_pos_mul = max_pos_gap // min_gap
-    max_neg_mul = max_neg_gap // min_gap
-    return st.one_of(
-        st.integers(0, max_pos_mul).map(lambda n: start + min_gap * n),
-        st.integers(0, max_neg_mul).map(lambda n: start - min_gap * n),
-    )
-
-
 @given(
     num=hh.sizes,
-    dtype=st.none() | xps.numeric_dtypes(),
+    dtype=st.none() | xps.floating_dtypes(),
     endpoint=st.booleans(),
     data=st.data(),
 )
 def test_linspace(num, dtype, endpoint, data):
     _dtype = dh.default_float if dtype is None else dtype
 
     start = data.draw(xps.from_dtype(_dtype, **finite_kw), label="start")
-    if dh.is_float_dtype(_dtype):
-        stop = data.draw(xps.from_dtype(_dtype, **finite_kw), label="stop")
-        # avoid overflow errors
-        assume(not ah.isnan(ah.asarray(stop - start, dtype=_dtype)))
-        assume(not ah.isnan(ah.asarray(start - stop, dtype=_dtype)))
-    else:
-        if num == 0:
-            stop = start
-        else:
-            stop = data.draw(int_stops(start, num, _dtype, endpoint), label="stop")
+    stop = data.draw(xps.from_dtype(_dtype, **finite_kw), label="stop")
+    # avoid overflow errors
+    assume(not ah.isnan(ah.asarray(stop - start, dtype=_dtype)))
+    assume(not ah.isnan(ah.asarray(start - stop, dtype=_dtype)))
 
     kw = data.draw(
         hh.specified_kwargs(

array_api_tests/test_linalg.py

@@ -315,7 +315,7 @@ def test_matmul(x1, x2):
 @given(
     x=finite_matrices(),
     kw=kwargs(keepdims=booleans(),
-              ord=sampled_from([-float('inf'), -2, -2, 1, 2, float('inf'), 'fro', 'nuc']))
+              ord=sampled_from([-float('inf'), -2, -1, 1, 2, float('inf'), 'fro', 'nuc']))
 )
 def test_matrix_norm(x, kw):
     res = linalg.matrix_norm(x, **kw)